Coronary Vasomotor Dysfunction Is Associated With Cardiovascular Events in Patients With Nonobstructive Coronary Artery Disease.

BACKGROUND: Coronary vasomotor dysfunction (CVDys) can be comprehensively classified on the basis of anatomy and functional mechanisms. OBJECTIVES: The aim of this study was to evaluate the association between different CVDys phenotypes and outcomes in patients with angina and nonobstructive coronary artery disease (ANOCA). METHODS: Patients with ANOCA who underwent coronary reactivity testing using an intracoronary Doppler guidewire to assess microvascular and epicardial coronary endothelium-dependent and endothelium-independent function were enrolled. Endothelium-dependent microvascular and epicardial coronary dysfunction were defined as a <50% change in coronary blood flow in response to intracoronary acetylcholine (Ach) infusion and a <-20% change in coronary artery diameter in response to Ach. Endothelium-independent microvascular and epicardial coronary dysfunction were defined as coronary flow reserve < 2.5 during adenosine-induced hyperemia and change in cross-sectional area in response to intracoronary nitroglycerin administration < 20%. Major adverse cardiac and cerebrovascular events (cardiovascular death, nonfatal MI, heart failure, stroke, and late revascularization) served as clinical outcomes. RESULTS: Among the 1,196 patients with ANOCA, the prevalence of CVDys was 24.5% and 51.8% among those with endothelium-independent and endothelium-dependent microvascular dysfunction, respectively, and 47.4% and 25.4% among those with endothelium-independent and endothelium-dependent epicardial coronary dysfunction, respectively. During 6.3 years (Q1-Q3: 2.5-12.9 years) of follow-up, patients with endothelium-dependent microvascular dysfunction, endothelium-dependent epicardial coronary dysfunction, or endothelium-independent microvascular dysfunction showed significantly higher event rates compared with those without (19.5% vs 12.0% [P < 0.001], 19.7% vs 14.6% [P = 0.038] and 22.2% vs 13.8% [P = 0.001], respectively). Coronary flow reserve (HR: 0.757; 95% CI: 0.604-0.957) and percentage change in coronary blood flow in response to Ach infusion (HR: 0.998; 95% CI: 0.996-0.999) remained significant predictors of major adverse cardiac and cerebrovascular event after adjustment for conventional risk factors. CONCLUSIONS: CVDys phenotype is differentially associated with worse outcomes, and endothelium-dependent and endothelium-independent microvascular function provide independent prognostic information in patients with ANOCA.

Circulating progenitor cells are associated with plaque progression and long-term outcomes in heart transplant patients.

AIMS: Circulating progenitor cells (CPCs) play a role in vascular repair and plaque stability, while osteocalcin (OC) expressing CPCs have been linked to unstable plaque and adverse cardiovascular outcomes. However, their role in cardiac allograft vasculopathy (CAV) has not been elucidated. This cohort study aimed to investigate the contribution of CPCs on CAV progression and cardiovascular events after heart transplantation. METHODS AND RESULTS: A total of 80 heart transplant patients (mean age 55 ± 14 years, 72% male) undergoing annual intravascular ultrasound (IVUS) had fresh CPCs marked by CD34, CD133, and OC counted in peripheral blood using flow cytometry, on the same day as baseline IVUS. CAV progression was assessed by IVUS as the change (Δ) in plaque volume divided by segment length (PV/SL), adjusted for the time between IVUS measurements [median 3.0, interquartile range (2.8-3.1) years] and was defined as ΔPV/SL that is above the median ΔPV/SL of study population. Major adverse cardiac events (MACEs) were defined as any incident of revascularization, myocardial infarction, heart failure admission, re-transplantation, stroke, and death. Patients with higher CD34+CD133+ CPCs had a decreased risk of CAV progression [odds ratio 0.58, 95% confidence interval (CI) (0.37-0.92), P = 0.01] and MACE [hazard ratio (HR) 0.79, 95% CI (0.66-0.99), P = 0.05] during a median (interquartile range) follow-up of 8.0 years (7.2-8.3). Contrarily, higher OC+ cell counts were associated with an increased risk of MACE [HR 1.26, 95% CI (1.03-1.57), P = 0.02]. CONCLUSIONS: Lower levels of CD34+CD133+ CPCs are associated with plaque progression and adverse long-term outcomes in patients who underwent allograft heart transplantation. In contrast, higher circulating OC+ levels are associated with adverse long-term outcomes. Thus, CPCs might play a role in amelioration of transplant vasculopathy, while OC expression by these cells might play a role in progression.

Machine learning aids clinical decision-making in patients presenting with angina and non-obstructive coronary artery disease.

Aims: The current gold standard comprehensive assessment of coronary microvascular dysfunction (CMD) is through a limited-access invasive catheterization lab procedure. We aimed to develop a point-of-care tool to assist clinical guidance in patients presenting with chest pain and/or an abnormal cardiac functional stress test and with non-obstructive coronary artery disease (NOCAD). Methods and results: This study included 1893 NOCAD patients (<50% angiographic stenosis) who underwent CMD evaluation as well as an electrocardiogram (ECG) up to 1-year prior. Endothelial-independent CMD was defined by coronary flow reserve (CFR) ≤2.5 in response to intracoronary adenosine. Endothelial-dependent CMD was defined by a maximal percent increase in coronary blood flow (%ΔCBF) ≤50% in response to intracoronary acetylcholine infusion. We trained algorithms to distinguish between the following outcomes: CFR ≤2.5, %ΔCBF ≤50, and the combination of both. Two classes of algorithms were trained, one depending on ECG waveforms as input, and another using tabular clinical data. Mean age was 51 ± 12 years and 66% were females (n = 1257). Area under the curve values ranged from 0.49 to 0.67 for all the outcomes. The best performance in our analysis was for the outcome CFR ≤2.5 with clinical variables. Area under the curve and accuracy were 0.67% and 60%. When decreasing the threshold of positivity, sensitivity and negative predictive value increased to 92% and 90%, respectively, while specificity and positive predictive value decreased to 25% and 29%, respectively. Conclusion: An artificial intelligence-enabled algorithm may be able to assist clinical guidance by ruling out CMD in patients presenting with chest pain and/or an abnormal functional stress test. This algorithm needs to be prospectively validated in different cohorts.